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Multistate models for comparing trends in hospitalizations among young adult survivors of colorectal cancer and matched controls.

Sutradhar R, Forbes S, Urbach DR, Paszat L, Rabeneck L, Baxter NN - BMC Health Serv Res (2012)

Bottom Line: However, among patients that have experienced one and two hospitalizations, the relative rate of a subsequent admission decreases to 3.03 (95% CI (2.01, 4.56)) and 1.90 (95% CI (1.19, 3.03)), respectively.However this relative risk decreases as the number of prior hospitalizations increases.The multistate approach is able to use information on the timing of hospitalizations and answer questions that standard Poisson and Negative Binomial models are unable to address.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada. rinku.sutradhar@ices.on.ca

ABSTRACT

Background: Over the past years, the incidence of colorectal cancer has been increasing among young adults. A large percentage of these patients live at least 5 years after diagnosis, but it is unknown whether their rate of hospitalizations after this 5-year mark is comparable to the general population.

Methods: This is a population-based cohort consisting of 917 young adult survivors diagnosed with colorectal cancer in Ontario from 1992-1999 and 4585 matched cancer-free controls. A multistate model is presented to reflect and compare trends in the hospitalization process among survivors and their matched controls.

Results: Analyses under a multistate model indicate that the risk of a subsequent hospital admission increases as the number of prior hospitalizations increases. Among patients who are yet to experience a hospitalization, the rate of admission is 3.47 times higher for YAS than controls (95% CI (2.79, 4.31)). However, among patients that have experienced one and two hospitalizations, the relative rate of a subsequent admission decreases to 3.03 (95% CI (2.01, 4.56)) and 1.90 (95% CI (1.19, 3.03)), respectively.

Conclusions: Young adult survivors of colorectal cancer have an increased risk of experiencing hospitalizations compared to cancer-free controls. However this relative risk decreases as the number of prior hospitalizations increases. The multistate approach is able to use information on the timing of hospitalizations and answer questions that standard Poisson and Negative Binomial models are unable to address.

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Multistate Diagram for Admissions and Death.
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Figure 1: Multistate Diagram for Admissions and Death.

Mentions: Function λi,js(t) represents the instantaneous rate for a transition from state j to state s at time t for the ith patient. The baseline instantaneous transition rate function λ0, js(t) and parameter vector βjs is specific to each j→s transition. The random effect νi accounts for the heterogeneity in the j→s transitions rates between patients [20]. Note that if we are interested in the estimate of a common regression parameter, then parameter vector βjs in the model can simply be replaced by β. Figure 1 provides a multistate diagram for characterizing the occurrence of hospital admissions and death. Patients in state 2, for example, are alive and have experienced two admissions; patients are in state D if they have died. From each non-absorbing state, patients can either make a forward transition to the next non-absorbing state or can make a transition to death. All models/graphs were run and created using the statistical package R [21].


Multistate models for comparing trends in hospitalizations among young adult survivors of colorectal cancer and matched controls.

Sutradhar R, Forbes S, Urbach DR, Paszat L, Rabeneck L, Baxter NN - BMC Health Serv Res (2012)

Multistate Diagram for Admissions and Death.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472287&req=5

Figure 1: Multistate Diagram for Admissions and Death.
Mentions: Function λi,js(t) represents the instantaneous rate for a transition from state j to state s at time t for the ith patient. The baseline instantaneous transition rate function λ0, js(t) and parameter vector βjs is specific to each j→s transition. The random effect νi accounts for the heterogeneity in the j→s transitions rates between patients [20]. Note that if we are interested in the estimate of a common regression parameter, then parameter vector βjs in the model can simply be replaced by β. Figure 1 provides a multistate diagram for characterizing the occurrence of hospital admissions and death. Patients in state 2, for example, are alive and have experienced two admissions; patients are in state D if they have died. From each non-absorbing state, patients can either make a forward transition to the next non-absorbing state or can make a transition to death. All models/graphs were run and created using the statistical package R [21].

Bottom Line: However, among patients that have experienced one and two hospitalizations, the relative rate of a subsequent admission decreases to 3.03 (95% CI (2.01, 4.56)) and 1.90 (95% CI (1.19, 3.03)), respectively.However this relative risk decreases as the number of prior hospitalizations increases.The multistate approach is able to use information on the timing of hospitalizations and answer questions that standard Poisson and Negative Binomial models are unable to address.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada. rinku.sutradhar@ices.on.ca

ABSTRACT

Background: Over the past years, the incidence of colorectal cancer has been increasing among young adults. A large percentage of these patients live at least 5 years after diagnosis, but it is unknown whether their rate of hospitalizations after this 5-year mark is comparable to the general population.

Methods: This is a population-based cohort consisting of 917 young adult survivors diagnosed with colorectal cancer in Ontario from 1992-1999 and 4585 matched cancer-free controls. A multistate model is presented to reflect and compare trends in the hospitalization process among survivors and their matched controls.

Results: Analyses under a multistate model indicate that the risk of a subsequent hospital admission increases as the number of prior hospitalizations increases. Among patients who are yet to experience a hospitalization, the rate of admission is 3.47 times higher for YAS than controls (95% CI (2.79, 4.31)). However, among patients that have experienced one and two hospitalizations, the relative rate of a subsequent admission decreases to 3.03 (95% CI (2.01, 4.56)) and 1.90 (95% CI (1.19, 3.03)), respectively.

Conclusions: Young adult survivors of colorectal cancer have an increased risk of experiencing hospitalizations compared to cancer-free controls. However this relative risk decreases as the number of prior hospitalizations increases. The multistate approach is able to use information on the timing of hospitalizations and answer questions that standard Poisson and Negative Binomial models are unable to address.

Show MeSH
Related in: MedlinePlus